System, method, and nanorobot to explore subterranean geophysical formations

ABSTRACT

An system and method for exploring geophysical formations at great depths below the surface of the earth. In order to explore the formation, nanorobots with a size less than 500 nanometers are inserted into the formation. The nanorobots propel through the formation, analyzing fluids and conditions as each moves through the formation. The nanorobots can communicate with a machine on the surface via a series of receivers and transmitters located in the wellbore. The machine on the surface is able to combine and analyze the data from the nanorobots to create a three dimensional map of the formation. The map shows the locations of pathways through the formation, pockets of hydrocarbons within the formation, and the boundaries of the formation.

This patent application claims priority to U.S. Provisional PatentApplication Ser. No. 61/159,943 filed on Mar. 13, 2009, which isincorporated by reference in its entirety.

BACKGROUND OF THE INVENTION

1. Field of the Invention

This invention generally relates to the field of exploring undergroundrock and hydrocarbon formations. In particular, the present invention isdirected to a method and apparatus for using nanorobots to move througha subsurface formation to identify various geophysical characteristics.

2. Description of the Related Art

The overriding problem in exploring for hydrocarbons in the subsurfaceis the probing in, and characterizing of, an environment that cannot beseen. Similarly once a commercial hydrocarbon deposit has beendiscovered and is about to be developed and exploited much conjectureand many assumptions must be made by reservoir geologists and reservoirengineers in the modeling of a large volume of rock which cannot beseen.

Subsurface reservoir data is currently acquired from probes lowered intoboreholes and from images (seismography). In the first instance, thedata is handicapped by its insufficiency, by virtue of being sourcedfrom a single 6-inch hole, thus giving too narrow of a view. Theinterpreted seismic volumes, on the other hand, gives too broad of aview due to their imaging quality and resolution inadequacies. Evencombining the two, will not enable for the mapping of exact highpermeability pathways.

The integration of available geological, geophysical, petrophysicalengineering, and drilling data makes interesting inroads into thedetection, mapping and predictive modeling of high permeabilitypathways. The final uncertainty of integrated models, however, can onlybe marginally better than the average uncertainty inherent in thevarious methods used. Mix and integrate as much as one may, the broadbrush strokes on reservoir map deliverables, will remain just that:broad brush. A 0.5 mm scribble drawn on a 1:200,000 scale map torepresent a fracture in the subsurface, is akin to depicting a fracturewith an aperture of 200 m because of the width of the scribble relativeto the scale of the map. The scribble will not reveal the precise paththat the fluids are likely to take.

As oil fields mature, it can be expected that fluid injection forpressure support (secondary enhanced oil recovery) will increasinglytend to erratically invade, and irregularly sweep, the residual oil leg.At the close of the second millennium, petroleum concerns were seenscrambling to mobilize however possible in order to identify, detect andmap pathways that may lead injected fluids prematurely updip alongencroachment fingers. More often than not, the encroachment materializesfaster than even the worst expectations, and commonly in quiteunpredictable directions. Moreover, premature encroachment is commonlytortuous and will change direction in 3D volume, much like a rubber ballwildly bounced about in a cubic enclosure. This type of tortuousityrenders high permeability pathway prediction almost impossible tosatisfactorily pin down. In spite of an arsenal of cutting-edgetechnologies thrown at such problems, high permeability pathwayprediction capability continues to suffer from high levels ofuncertainty.

Post mortem and predictive mapping of erratically occurring highpermeability pathways is a leading issue of concern to major petroleumcompanies. The solution to the problem is currently sought through themanipulation of data acquired directly from the borehole and indirectly,through map view representations of faults or fracture swarms orhorizontal permeability (“kh”) from pressure buildups. Permeabilitypathways are interwell phenomena. Unfortunately, it is interwell controlthat is very difficult to characterize.

With current technology, it is impossible to work out the exact pathwaythat fluid fingering takes as it invades deep into an oil leg, much lesswhere it will go next. Engineering data (e.g. water arrival data—i.e.,water arrival detected in an oil producing well, flowmeter data, test khbuild-up, pressure data, and productivity/infectivity data), althoughmostly acquired at the borehole, are typically correlated aerially. Theresultant maps are a very indirect, unreliable and a crude way of tryingto depict the reservoir geology of a reservoir. The resultant maps areinterpretive, and reservoir engineers are the first to dissociate themfrom being accurate reflections of specific geologic features. Moreover,the map resolutions are too broad to even remotely represent mostgeological features that would commonly be associated with highpermeability pathways.

Other interwell methods to map permeability pathways are, likewise,handicapped by resolution problems. Geophysical technologies rooted ininterpreting 3D, 4D, shear wave, or multi-component volumes; even whenutilizing ever-developing clarity and resolution enhancing softwarepackages, still only render a generalized mapping of a minisculesampling of some faults in the general area where they may or may not belocated.

In carbonate rocks, fractures with apertures measured in millimeters, orgeobodies only centimeters across, can provide the necessary plumbing totake injected fluid past matrixed oil. To further illustrate this, a 3cm wide fracture with no displacement may, under pressure, move fluidsat several Darcies. These dimensions cannot be seen by currentinterpretive geophysical devices. Subsequently, the fault lines drawn onreservoir structure maps cannot be considered more than broad arrowspointing out a general direction; and not a depiction of actualpermeability pathways. Furthermore, geophysically-interpreted data mustbe augmented by a solid understanding of the regional stress-strainregimes in order to filter out fracture swarms which may not becontributing to premature fluid breakthroughs.

Dyes and radioactive chemicals (tracers) introduced with injected fluidscan be locally helpful, but they will not reveal the actual pathwaytaken by the host fluid from the entry well to the detection well.Borehole detection methods are the most exact, but they are alsoafflicted with major shortcomings. The immediately obvious shortcomingis that, for mapping purposes, wellsite data must be extrapolated andtransformed into interwell information. Extrapolation in itself is theproblem.

Any sedimentologist will sympathize with the deposition heterogeneitieswith or without a structural overprint. The slightest shifts in waterdepth, measured in decimeters, can create worlds of difference indepositional fabric. Moreover, rock minerals, especially carbonates, arein continuous “life long” effective diagenesis from the instant ofdeposition. There is no carbonate porosity that has not been dictated bydeposition and then unceasingly altered by diagenesis. One can alreadysee the problem of interwell extrapolation from well control.

The geostatistical distribution of attributes, including fracturesdetected on borehole image logs, at the wellbore, is the best we've got;but it is only statistical, and natural geological landscapes are toovariable and rugose to respond comfortably to the smooth, clean logic ofmathematics. Much like fingerprints, there are no two features incarbonate rocks that are the same. Extrapolation in the complex world ofcarbonate geology has a long way to go.

Adding to the difficulties of borehole solutions is that the geologicalfeatures contributing to abnormally high flow rates are, like some rarespecies, rarely captured in rock cores. Consequently reservoirgeologists are, in most cases, disallowed the opportunity to properlystudy and characterize reservoir problems.

SUMMARY OF THE INVENTION

A geophysical formation can include large rock formations. The rockformations are not solid (like metals), rather, they are a series ofinterconnected pores and pathways. Many of these pores and pathways areless than 1000 nanometers wide. The pores can contain a variety offluids including oil, water, or natural gas.

It is desirable to know the contents and the structure of the pores. Itis also important to understand the structures that permit high speedfluid flow through the formation. These “pathways” are important becausewater used to push the hydrocarbons through the formation, whethernatural water-drive water or injected water, can flow from the watersource, through the pathway to the wellbore, thus bypassing pockets ofhydrocarbons.

Due to the depth of hydrocarbon bearing formations, often severalthousand feet below ground, it is difficult to map a series ofmicroscopic pores. Conventional devices for determining the contents ofthe formation, as shown in FIG. 1, are not effective for mapping thepore structure or learning the contents of the pores. One such method issurface seismic analysis, in which loud noises such as explosive chargesare created near the surface, and an array of acoustic receivers 20measure and record the reflected sound. Similarly, acoustic receivers 22can be lowered into a wellbore 100 to record reflected sound. Neither ofthese seismic methods provide any detail about the pore structure northe specific locations of the pores. Another method is to drill awellbore 100 and remove core samples from the area drilled. The coresamples are only a few inches wide and do not reveal the pathwaystructure for the entire geophysical formation.

A nanoscale robot, with a dimension smaller than 500 nanometers, couldmove through the pores to map the pore and pathway structure, findhydrocarbons within the structure, find water within the structure, andanalyze the fluids, minerals, and rocks within the structure. Thegeophysical exploration nanorobots move through the hydrocarbonreservoir and, thus, may be called “Resbots”™.

One embodiment of a system to measure properties in a geophysicalincludes a wellbore lining in a wellbore, a plurality of fixed radiofrequency receivers spaced apart along the longitudinal extent of andassociated with the wellbore lining to receive radio frequencytransmissions at one or more preselected radio frequencies, and aplurality of independent and untethered robots positioned within thegeophysical formation. Each of the plurality of independent anduntethered robots includes a robot body formed of a plurality of carbonnanotubes adapted to withstand temperatures exceeding 300 degreesFahrenheit and being sized so that none of the length, width, or heightof the robot body is greater than 500 nanometers, a sensor associatedwith the robot body and positioned to detect the presence of one or morehydrocarbons within the geophysical formation, a radio frequencytransmitter associated with the robot body, positioned to transmitpositional data and hydrocarbon characteristic data from the geophysicalformation when the robot is positioned therein, and a power supplyassociated with the robot body to supply power to the transmitter andthe sensor. These parts of the independent and untethered robot cancollectively define a geophysical nanorobots. In this embodiment, thesystem also includes a machine in communication with each of theplurality of geophysical nanorobots, the machine including a processor,a display in communication with the processor, and a non-transitory,computer-readable storage medium with an executable program storedtherein, wherein the program instructs the processor to perform thefollowing steps: receiving positional data from one or more of theplurality of geophysical nanorobots, the positional data indicating thelocation of the geophysical nanorobots at a point in time; plotting,responsive to receipt of the positional data, at least one positionaldata point for one or more of the plurality of geophysical nanorobots toindicate a location of a cavity accessible by a geophysical nanorobots;receiving interior surface location data from one or more of theplurality of geophysical nanorobots, the interior surface location datadefining a sensed three dimensional location of at least one point on aninterior surface within the geophysical formation; combining the surfacelocation data from the one or more of the plurality of geophysicalnanorobots to create a representation of a physical map of at least aportion of the geophysical formation, the physical map indicating thethree dimensional location of each of the plurality of sensed threedimensional locations within an interior surface of the geophysicalformation; generating an interpolated map by projecting surfaces betweena plurality of the points of the physical map, the interpolated mapidentifying a plurality of cavities in fluid communication with adjacentcavities; receiving fluid data from one or more of the plurality ofgeophysical nanorobots, the fluid data indicating the type and locationof fluid located at each of a plurality of locations within thegeophysical formation; and creating a fluid map on the display byplotting the type and location of fluids onto the interpolated map.

In another embodiment, the system includes a molecular processorassociated with the robot body and responsive to the sensor to processdetected hydrocarbon data from the sensor, and the radio frequencytransmitter associated with the robot body is responsive to themolecular processor and positioned to transmit hydrocarboncharacteristic data to one or more of the plurality of fixedradiofrequency receivers.

In another embodiment, the system includes a geophysical nanorobotcarrier adapted to carry and transport the plurality of geophysicalnanorobots into the wellbore when positioned adjacent thereto, thegeophysical nanorobot carrier being a wellbore lining having a pluralityof perforations therein through which the plurality of geophysicalrobots pass when being inserted into the geophysical formation.

In another embodiment, at least one of the fixed radio frequencyreceivers is positioned to receive data from at least another one of thefixed radio frequency receivers when positioned in the geophysicalformation and re-transmit the data from the at least another one of thefixed radio frequency receivers to the machine.

In another embodiment, each of the nanorobots also includes a propulsiondevice associated with each of the robot bodies to propel each of theplurality of geophysical nanorobots through pathways within thegeophysical formation.

Another embodiment includes a plurality of fixed radio transmittersassociated with the wellbore lining. Each of the plurality ofgeophysical nanorobots also includes a payload bay having a payload; andthe geophysical nanorobot is positioned to release the payload inresponse to a signal from one of the plurality of fixed radiotransmitters.

In another embodiment, the propulsion device of each of the plurality ofgeophysical nanorobots can include one or more of the following: apropeller, a flagella, a membrane, a crawler, and a Brownian motor. Inanother embodiment, the power supply of each of the plurality ofgeophysical nanorobots can derive energy from a fluid within thegeophysical formation. In yet another embodiment, the power supply ofeach of the plurality of geophysical nanorobots can include one or moreof the following: a fuel cell, wherein the fuel cell derives power fromin-situ hydrocarbons; a thermoelectric power supply, wherein the heat ofthe fluid within the geophysical formation generates electricity; apiezoelectric generator, wherein the compressive forces acting on thepiezoelectric generator generate electricity; an electromechanicalnanoactuator responsive to movement of the fluid; and an ATPasecatalyst, wherein the ATPase catalyst causes a chemical within the fluidto decompose and wherein energy is released when the chemical within thefluid decomposes. In another embodiment, the sensor can of each of theplurality of geophysical nanorobots can sense one or more of thefollowing: fluid type, temperature, pressure, petrophysical property,geophysical nanorobot trajectory, and geophysical nanorobot position.

Another embodiment includes a plurality of fixed radio transmittersassociated with the wellbore lining and each of the plurality ofgeophysical nanorobots also includes a nanorobot radio frequencyreceiver associated therewith; and one or more of the plurality ofnanorobots propels in a direction different than a current trajectory inresponse to instructions from the machine transmitted via the pluralityof fixed radio transmitters.

Another embodiment includes a battery charger associated with thewellbore lining which defines a downhole charging station; and each ofthe plurality of geophysical nanorobots also includes a carbon nanotubebased battery located in the robot body. Each of the plurality ofgeophysical nanorobots can propel to the proximity of the downholecharging station and the downhole charging station charges each of thecarbon nanotube based batteries.

Another embodiment includes a plurality of radio directionaltransmitters associated with the wellbore lining, each transmitting abeacon therefrom, wherein each of the plurality of geophysicalnanorobots also includes a nanorobot radio frequency receiver, andwherein each of the plurality of geophysical nanorobots determines itsposition in response to signals from the plurality of radio directionbeacons. In another embodiment, each of the plurality of geophysicalnanorobots also includes a nanorobot radio frequency receiver, whereinone or more of the plurality of geophysical nanorobots is positioned toreceive positional data from at least another one of the plurality ofgeophysical nanorobots and re-transmit the positional data from the atleast another one of the plurality of geophysical nanorobots.

In another embodiment, the surface location data includes the locationof a point wherein one of the plurality of geophysical nanorobotscontacted a surface within the geophysical formation. In anotherembodiment, the surface location data includes multiple location pointsfrom non-contact sensors. In another embodiment, the non-contact sensorsinclude an ultrasonic sensor or a radio frequency sensor, or both,located on the geophysical nanorobots.

In another embodiment, the program further instructs the processor toperform the step of interpolating fluid data to identify athree-dimensional region filled with a homogenous fluid to define afluid pocket within the geophysical formation. In another embodiment,the program also instructs the processor to perform the step ofidentifying a plurality of cavities in communication with one another,each cavity having a cross-sectional area greater than a predeterminedvalue, to define a pathway.

In another embodiment, the program also instructs the processor toperform the step of identifying a pocket having a homogenous hydrocarbonthat is generally surrounded by a fluid that is different than thehomogenous hydrocarbon to define a hydrocarbon pocket within thegeophysical formation. In another embodiment, the program also instructsthe processor to perform the step of causing at least one of theplurality of geophysical nanorobots to move to a location different thanits current location.

One embodiment of a technique to identify properties of a geophysicalformation includes steps of: communicating, to a machine, the machineincluding a processor, a display in communication with the processor,and a non-transitory, computer-readable storage medium with anexecutable program stored therein, interior surface location data of thegeophysical formation from a plurality of geophysical robots, theinterior surface location data defining a sensed three dimensionallocation of at least one point on each of a plurality of interiorsurfaces within the geophysical formation; generating an interpolatedmap on the machine, responsive to the interior surface location data, byprojecting surfaces between representations of the at least one pointson each of the plurality of interior surfaces of the geophysicalformation, the interpolated map identifying a physical shape and alocation of a plurality of surfaces in the geophysical formation;communicating, to the machine, fluid data responsive to a sensor locatedon each of the one or more of the plurality of geophysical robots, thefluid data indicating the type and location of fluid located at each ofa plurality of locations within the geophysical formation; and creatinga fluid map on the machine by plotting the type and location of fluidsonto the interpolated map of the geophysical formation so that physicalrepresentation of fluids within the geophysical formation are displayedon the machine.

In another embodiment, the technique includes interpolating, by themachine, the fluid data to identify a three-dimensional region filledwith a homogenous fluid to define a fluid pocket within the geophysicalformation. In another embodiment, the technique includes identifying, bythe machine, a plurality of cavities in communication with one another,each cavity having a cross-sectional area greater than a predeterminedvalue, to define a pathway.

In another embodiment of the technique, the plurality of geophysicalrobots include a nanorobot defined as having: a robot body formed of aplurality of carbon nanotubes adapted to withstand temperaturesexceeding 300 degrees Fahrenheit and being sized so that none of thelength, width, or height of the robot body is greater than 500nanometers, a hydrocarbon sensor associated with the robot body andpositioned to detect the presence of one or more hydrocarbons within thegeophysical formation, a radio frequency receiver associated with therobot body, positioned to receive radio frequency transmissions, a radiofrequency transmitter associated with the robot body, positioned totransmit positional data and hydrocarbon characteristic data from thegeophysical formation when the robot is positioned therein, and a powersupply associated with the robot body to supply power to the receiver,the transmitter, and the sensor.

In another embodiment, the communicating step of the technique includestransmitting, via a radio frequency transmitter associated with therobot body, to a fixed radio frequency receiver located in a wellbore.In another embodiment, the communicating step of the technique includestransmitting data, via a fixed radio frequency transmitter associatedwith a wellbore, to a fixed radio frequency receiver associated with thewellbore and further communicating the data to the machine.

In another embodiment, a system to measure properties in a geophysicalformation includes a plurality of wellbore linings each being positionedin a separate and different one of a plurality of wellbores extendinginto a geophysical formation. It also includes a plurality of fixedradio frequency transmitters spaced apart along the longitudinal extentof and associated with one or more of the plurality of wellbore liningsto transmit radio frequency signals at one or more preselected radiofrequencies and a plurality of independent and untethered robotspositioned within the geophysical formation. Each of the plurality ofindependent and untethered robots can include a robot body having adiameter no greater than 1000 nanometers, formed of a plurality ofcarbon nanotubes adapted to withstand temperatures exceeding 300 degreesFahrenheit, and a radio frequency identification tag positioned totransmit a signal responsive to the one or more preselected radiofrequency signal transmitted by one or more of the plurality of fixedtransmitters. Thus, the plurality of independent and untethered robotscan collectively define a plurality of geophysical nanorobots. Thesystem can also include a plurality of fixed radio frequency receiverspositioned spaced apart along the longitudinal extent of and associatedwith one or more of the plurality of wellbore linings to receive radiofrequency signals at one or more preselected radio frequencies, amachine in communication with each of the plurality of geophysicalnanorobots, the machine including a processor, a display incommunication with the processor, and a non-transitory,computer-readable storage medium with an executable program storedtherein. The program product can instruct the processor to perform thefollowing steps: receiving positional data from one or more of theplurality of geophysical nanorobots, the positional data indicating thelocation of the geophysical nanorobots at a point in time; plotting,responsive to receipt of the positional data, at least one positionaldata point for a portion the plurality of geophysical nanorobots toindicate a location of a cavity accessible by one of the plurality ofgeophysical nanorobots; and combining the positional data points of aportion of the plurality of geophysical nanorobots to create arepresentation of a physical map of at least a portion of thegeophysical formation, the physical map indicating the three-dimensionallocation of each cavity of the geophysical formation accessible by oneof the plurality of nanorobots.

In another embodiment, each of the plurality of geophysical nanorobotshas a substantially spherical shape and the program further instructsthe processor to perform the steps of identifying a plurality ofcavities in communication with one another, each cavity having across-sectional area located between outer walls of the cavity,transverse to a travel path of the geophysical nanorobot, greater than apredetermined value, to define a pathway responsive to thethree-dimensional location of each cavity indicated on the physical map.The program can instruct the computer to cause a portion of theplurality of geophysical nanorobots, located within the pathway, torelease the payload contained therein within the pathway.

In another embodiment, the body of each of the plurality of geophysicalnanorobots has a substantially spherical shape and the plurality ofgeophysical nanorobots also has a plurality of different sizeddiameters. The program further instructs the processor to perform thestep of identifying a location within the formation accessible to afirst set of the plurality of geophysical nanorobots having one of thedifferent sized diameters, not readily accessible to a second set ofgeophysical nanorobots having another one of the different sizeddiameters.

BRIEF DESCRIPTION OF THE DRAWINGS

So that the manner in which the features, advantages and objects of theinvention, as well as others which will become apparent, are attainedand can be understood in more detail, more particular description of theinvention briefly summarized above may be had by reference to theembodiment thereof which is illustrated in the attached drawings, whichdrawings form a part of this specification. It is to be noted, however,that the drawings illustrate only a preferred embodiment of theinvention and therefore should not be considered limiting of its scopeas the invention may admit to other equally effective embodiments.

FIG. 1 is a partial sectional view of surface and downhole seismicmapping operations according to the prior art.

FIG. 2 is a partial sectional view of a geophysical nanorobot basedgeophysical exploration system according to an embodiment of the presentinvention.

FIG. 3 is an enlarged sectional view of a wellbore in a geophysicalformation having a plurality of geophysical nanorobots deployed throughfissures, pathways, and porous rock structures according to stillanother embodiment of the present invention.

FIG. 4 is a sectional view of a geophysical nanorobot having multiplepropulsion devices, a processor, a radio frequency transmitter, and asensor according to yet another embodiment of the present invention.

FIG. 5 is a partial sectional view of a geophysical nanorobot having anano-processor control system according to yet another embodiment of thepresent invention.

FIG. 6 is a partial sectional view of a geophysical nanorobot having aradio frequency transmitter and a vibration sensor according to yetanother embodiment of the present invention.

FIG. 7 is a flowchart of operational identification of fluid propertiesresponsive to a plurality of geophysical nanorobots according to anotherembodiment of the present invention.

FIG. 8A is a perspective view of a geophysical nanorobot having apropulsion device according to yet another embodiment of the presentinvention.

FIG. 8B is a perspective view of a geophysical nanorobot having apropulsion device according to yet another embodiment of the presentinvention.

FIG. 8C is a perspective view of a geophysical nanorobot having apropulsion device according to yet another embodiment of the presentinvention.

FIG. 8D is a perspective view of a geophysical nanorobot having apropulsion device according to yet another embodiment of the presentinvention.

FIG. 9 is a functional block diagram of a geophysical nanorobot basedgeographical exploration system according to an embodiment of thepresent invention.

FIG. 10 is a flowchart of operational propulsion of a plurality ofgeophysical nanorobots in a geophysical formation according to anotherembodiment of the present invention.

FIG. 11A is a sectional view of a geophysical nanorobot performingcontact mapping according to yet another embodiment of the presentinvention.

FIG. 11B is a depiction of a map developed from the contact mapping ofFIG. 11A according to yet another embodiment of the present invention.

FIG. 12 is a sectional view of a geophysical nanorobot performingnon-contact mapping according to yet another embodiment of the presentinvention.

FIG. 13 is a perspective view of a geophysical nanorobot having apayload bay and a flagella propulsion device according to yet anotherembodiment of the present invention.

FIG. 14 is an environmental sectional view of a plurality of differentsized geophysical nanorobots, each having a spherical shape and a radiofrequency identification tag, located in pathways in a geophysicalformation according to another embodiment of the present invention.

FIG. 15 is an environmental sectional view of a system having aplurality of geophysical nanorobots that are injected with secondaryrecovery pressurized water according to another embodiment of thepresent invention.

FIG. 16 is a partial sectional view of a carrier inserting a pluralityof geophysical nanorobots to pass through perforations in wellborecasing of a wellbore according to another embodiment of the presentinvention.

FIG. 17 is a flowchart of operational insertion of a plurality ofgeophysical nanorobots into a geophysical formation according to anotherembodiment of the present invention.

FIG. 18 is a sectional view of the casing of the geophysical explorationsystem of FIG. 2 according to an embodiment of the present invention.

FIG. 19 is an environmental sectional view of a plurality of geophysicalnanorobots relaying transmissions to wellbore receivers according to yetanother embodiment of the present invention.

FIG. 20 is a partial sectional view of a geophysical nanorobot basedgeophysical exploration system according to yet another embodiment ofthe present invention.

FIG. 21 is a flowchart of a nanorobot based geophysical mappingoperation according to an embodiment of the present invention.

FIG. 22 is a functional block diagram of a computer to control aplurality of geophysical nanorobots and analyzing data from geophysicalnanorobots according to another embodiment of the present invention.

FIG. 23 is a flowchart of a controller operating a plurality ofgeophysical nanorobots according to another embodiment of the presentinvention.

FIG. 24 is a flowchart of operational mapping of a geophysical formationusing data from a plurality of geophysical nanorobots according toanother embodiment of the present invention.

FIG. 25 is a flowchart of operational mapping fluid formations usingdata from a plurality of geophysical nanorobots according to anotherembodiment of the present invention.

FIG. 26 is a flowchart of operational mapping pathways using data from aplurality of geophysical nanorobots according to another embodiment ofthe present invention.

FIG. 27 is a flowchart of operational locating of hydrocarbon formationsusing data from a plurality of geophysical nanorobots according toanother embodiment of the present invention.

FIG. 28 is a flowchart of operational mapping gas plumes using data froma plurality of geophysical nanorobots according to another embodiment ofthe present invention.

FIG. 29 is a flowchart of operational mapping potable water formationsusing data from a plurality of geophysical nanorobots according toanother embodiment of the present invention.

FIG. 30 is a flowchart of approximating surface locations from thepositions of geophysical nanorobots according to another embodiment ofthe present invention.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENT

The present invention will now be described more fully hereinafter withreference to the accompanying drawings which illustrate embodiments ofthe invention. This invention may, however, be embodied in manydifferent forms and should not be construed as limited to theillustrated embodiments set forth herein. Rather, these embodiments areprovided so that this disclosure will be thorough and complete, and willfully convey the scope of the invention to those skilled in the art.Like numbers refer to like elements throughout, and the prime notation,if used, indicates similar elements in alternative embodiments.

One or more wellbores 100 are drilled 510 into a geophysical formation102 (hereinafter “geophysical formation,” “formation,” or “rock”), asshown in FIGS. 2 and 3. A wellbore 100 can be an exploratory well usedto locate hydrocarbons 110 such as oil or gas 116, water, or otherfluids 112. The term “fluids” refers to any type of gas or liquid fluid,including water, hydrocarbons, and gas. If desirable fluids are found, awellbore 100 can be completed as a production well. Wellbore completionfrequently includes lining 512 the wellbore with a wellbore lining suchas, for example, casing 104, which is generally a metallic pipe or tube.The casing 104 can be cemented in place. Additional production wells 106can be drilled in the same geophysical formation. Wellbores can also beused for secondary recovery operations (FIG. 15). In a secondary ortertiary recovery operation, an injection fluid 108 such as water,steam, carbon dioxide, or chemicals are injected, under pressure, intothe geophysical formation 102. The injection fluid serves as a drivemechanism to push the well fluids out through a production well 100. Theproduction or injection well can be used to insert nanorobots into thegeophysical formation.

A geophysical nanorobot 114, or “Resbot™,” is a nanoscale probe that isable to travel deep within underground rock strata along pathwayspermeable to fluids and transmit back and/or collect data that can beused to map and characterize the pathways. In the instant specification,the term “robot” means a mechanical device that is capable of performingone or more tasks on command or by being programmed in advance; amachine or device that can be operated by remote control orautomatically. A nanorobot, thus, is a robot on a nano scale. In anexemplary embodiment, the nanorobots have at least one dimension lessthan 500 nanometers. Individual components in a nanorobot 114 cangenerally have dimensions of 1 to 100 nanometers. In some embodiments,all of the dimensions (length, width, height) are less than 500nanometers. One nanometer (nm) is one billionth, or 10⁻⁹, of a meter. Anexemplary embodiment of a nanorobot 114 is shown in FIG. 4. Thenanorobots 114 are small enough to fit through the pathways, pores, andfissures in the formations.

As shown in FIG. 3, the geophysical nanorobots 114 travel throughcavities 118, which includes pores and pathways 120, within thegeophysical formation 102. The cavities 118 depicted in FIG. 3 areenlarged to show detail. The pores and pathways inside the oil bearingrocks are very small, typically less than 1000 nanometers. A pathway 120can also be is less than 1000 nanometers wide, but could be larger than1000 nanometers wide. A nanorobot with a dimension less than 500 nm canfit through most of the pores and pathways within the formation.

The nanorobots 114, are deployed 518 into the geophysical formation 102(rock formation) to map the formation, find fluids 110 such ashydrocarbons 110, find bypassed pockets of fluids, water 116, mineralsolids, and voids. Once in the cavity 118 system of the targeted hostrock, the nanorobot 114 is propelled 522 along with the natural flow ofthe fluid medium within which it is traveling, and, in some embodiments,it as also able to thrust itself along using its own power. If thenanorobot is in the desired location to be mapped 524, it will proceedwith its analysis. In one embodiment, if the nanorobot is not in thecorrect location 524, an onboard controller 124 or above groundnanorobot control computer 126 can instruct the nanorobot to move to adifferent location 526. The nanorobot 114 can communicate with thecontrol computer 126 by using an onboard transmitter 128 and receiver130. The nanorobot can communicate with the control computer by sendingand receiving data through fixed receivers 134 and transmitters 136located in the wellbore 100, on the surface, or embedded in thegeophysical formation 102. The nanorobot 114 uses sensors 138 toidentify 528 and describe the fluids 112 it comes in contact with. Thenanorobot 114 also supports characterizing rock formations, by measuring530 dimensions and locations of subterranean features, including thesize of cavities 118 and the pathways 120 formed by interconnectedcavities 118. The overall process for the insertion, deployment,control, data transmission, and analysis is shown in FIG. 21, andreferenced throughout this document. A more detailed description of thisgeophysical nanorobot exploration system follows.

As illustrated in FIGS. 4-14, the nanorobots 114 can have sensors 138and an onboard computer 124. The onboard computer 124 controls theactions of the nanorobot 114 and can record data regarding thenanorobot's position and sensor 138 readings. In some embodiments, thenanorobot 114 is able to determine its coordinates and calculate itsvelocity at any given time. Some nanorobots have transmitters 128 forsending information and receivers 130 for receiving information. Someembodiments have a payload bay 140 and can deliver a payload 142, suchas a surfactant, to a location within the geophysical formation. In somenanorobots, the receiver 130 can receive data signals from fixedtransmitters 136 or from other nanorobots 114. Furthermore, the receiver130, or another receiver, can detect radio frequency or ultrasonicsignals. Each of these components will be described in greater detail.The nanorobots 114 can operate independently and without being tetheredto any other component.

The nanorobot is housed in a body 132 or shell, as shown in FIG. 4. Thebody is adherence-resistant and can be generally spherical (FIG. 14) orcapsule-shaped, but could be other shapes. The body 132 can have atapered shape, as shown in FIG. 6, or a cylindrical shape, as shown inFIGS. 8A-8D. The adherence resistance, among other things, prevents theviscous formation fluids from adhering to the nanorobot. The body 132can be hermetically sealed to protect the components inside the body 132from wellbore fluids 112. The body 132 houses the elements of thenanorobot and can serve as a frame for the elements. The body can bemade of any material that is suitable to the small scale of thenanorobot and that provides the required protection from the intendedoperating environment. The body material can be based upon, for example,carbon nanotubes (“CNT”) or Boron-Nitride. The carbon nanotubes can bebonded or otherwise fused together to form the body. The nanorobot 114can encounter temperatures in excess of 300 degrees Fahrenheit. The body132 is able to withstand temperatures in excess of 300 degrees and serveas a thermal protection shield for the other components of thenanorobot. The body 132, thus, allows the nanorobot to operate inenvironments in excess of 300 degrees Fahrenheit.

In one embodiment, shown in FIG. 14, a nanorobot 115 has a sphericalshape. In one embodiment, nanorobot 115 has a reactive identificationtag 133 that responds to an external signal. A wellbore fixedtransmitter 136, for example, could emit a signal that causes reactiveidentification tag 133 to emit a different signal, and the differentsignal can be received by one or more wellbore fixed receivers 134. Thereactive identification tag 133 could be, for example, a radio frequencyidentification tag that emits a unique radio frequency in response toreceiving a radio frequency. In one embodiment, the reactiveidentification tag 133 includes magnetic particles. The magneticparticles respond to electromagnetic energy emitted by the wellborefixed transmitters 136, and the presence of the magnetic particles isdetected by wellbore fixed receivers 134. In one embodiment, nanorobots115 have different sizes. Some could have a diameter, for example, lessthan 500 nanometers, and some could have a diameter, for example, of 750nanometers or 1000 nanometers.

As illustrated in FIGS. 4-14, the nanorobot 114 has one or more sensors138 for sensing its environment. In an exemplary embodiment, thenanorobot 114 has positional sensors that indicate its position withinthe rock formation, including its vertical position. The positionalsensor, or data from the positional sensor, can also detect thenanorobots 114 velocity as it moves through the formation. In someembodiments, an onboard computer 124 uses positional information tocalculate velocity and/or trajectory of the nanorobot 114. In otherembodiments, the onboard computer 124 can use data from directional andvelocity sensors to calculate position. In some embodiments, thepositional sensors can use external signals such as directional radiofrequency beacons to determine the position.

The nanorobot sensor 138 can include chemical and gas sensors and can becarbon nano tube (“CNT”) based. The chemical and gas sensors are capableof determining the composition of rocks and fluids. The onboard computer124, such as a nano-computer or molecular computer, can be used tointerpret sensor data and identify elements. In some embodiments, theraw sensor data is transmitted to the wellbore receiver and sent to ananorobot control computer 126 for interpretation.

The sensor 138 can include a fluid properties sensor and, thus, cansense fluid properties including the presence of a fluid, fluid type,temperature, pressure, and viscosity 528. In some embodiments, the fluidsensor can identify the presence of a hydrocarbon, identify the type ofhydrocarbon, or identify a particular liquid. Furthermore, in oneembodiment, the fluid type sensor can detect the presence and type ofnatural water drive fluids, injection fluids, and other fluids that maybe present in the rock formation. The fluid data can also indicate fluidsaturation within the geophysical formation. In one embodiment, sensor138 includes ligands that are chemically reactive to, for example,different fluid types, salinity, pH, and temperature. FIG. 7 is a flowchart showing examples of techniques to determine fluid properties usingsensors 138 on a nanorobot. The steps of FIG. 7 are referred tothroughout the discussion of sensors.

The nanorobot 124 must be in contact with a fluid 172. If it is not, theonboard computer 124 or control computer 126 can direct the nanorobot114 to a different location 174. In one embodiment, as shown in FIG. 4,the sensor 138 includes electrodes 146, 176 for determining fluidproperties. Electric current can be passed between the electrodes 178.The amount of resistance provided by the fluid can indicate the presenceof a fluid and the fluid type 180. Similarly, the resistance 192 from athermistor 148 (FIG. 5) can indicate the temperature 188 of a fluid incontact with the nanorobot 114, 190. The electrodes 146 and thermistor148 can be connected to the onboard computer 124. The electrodes 146 canalso be part of a pH sensor 182 for determining the pH of fluids.Electric current can be passed through the fluid between pH sensorelectrodes 184, and the amount of current passed through the fluid canindicate the hydrogen ion concentration in the fluid 186 and, thus,indicate the pH of the fluid.

In one embodiment, the nanorobot 114 includes a laboratory on a chip(“LOC”) 150 (FIG. 6). The LOC 150, also known as a“micro-total-analysis-system,” integrates several chemical orbio-chemical analysis steps on a single chip, wherein the chip is smallenough to fit inside a nanorobot. LOC analysis could include, forexample, measurement of reservoir (dynamic) fluid properties, productionallocation, formation stresses, pressures and borehole stability,formation damage assessment, mud rheology and mud logging, and formationevaluation. LOC analysis can also determine whether water is potable.LOC 150 may include ligands.

In some embodiments, one of the sensors 138 can include a nano camera torecord and ultimately transmit images from inside the formation. Othersensors can include a pressure sensor or a viscosity sensor. Forexample, the deflection of a pressure sensor 204 (FIG. 8A) can bemeasured 196 to determine the pressure of the fluid. The viscosity 198of a fluid can be measured by measuring the velocity of the nanorobotand comparing the velocity to the required propulsion power 200. Indeed,propulsion components, including, for example, propellers 166, vibratingmembranes 168, and flagella 170 can also be used to determine severalfluid properties. For example, the current required to drive any of thepropulsion devices can be indicators of viscosity 202. Furthermore, theresistance encountered by the vibrating membrane 168 can be an indicatorof pressure.

In some embodiments, the sensor 138 includes a rock composition sensorthat is able to determine the type of rock in contact with thenanorobot. The sensor can also determine, for example, the relativepermeability, pore throat size, porosity, permeability, and mineralstructure of the rocks 530. Other rock characteristics can also bemeasured. For example, sensors 138 on the nanorobot 114 can includesensors to measure physical dimensions such as the aperture of a cavity118, or pore, in a rock formation. A variety of sensors could be usedincluding, for example, positional, contact sensors, and non-contactsensors. Porosity, relative permeability, and mineral structure of thegeophysical formation 102 can be determined from sensed data.

In some embodiments, the pore width is measured by recording theposition of the nanorobot as it moves across the diameter of the pore118 along a path 156 (see FIG. 11A). The path 156 can be random ordeliberate movements within the pore 118. The surfaces 152 of the poreare identified each time the nanorobot contacts the surface 152 at apoint 154. The relative locations of the points 154 can be stored in thememory of the nanorobot computer 124, or can be transferred to thecontrol computer 126 for analysis. FIG. 11B shows a plot that can becreated from the contact points 154 of the nanorobot. Each point 154 isplotted relative to the other known contact points 154. The aperture orpore size can be calculated from the distance between the contact points154, and the overall cross-sectional area of the pore can be calculatedfrom the known points. The positional data of the nanorobot, thus, isanalyzed to determine the physical dimensions of the pore 118. In someembodiments, the nanorobot sensor 138 can detect contact with the rockto determine each contact point. In other embodiments, the nanorobot 114is propelled through the pore and stops or changes directions each timeit contacts a surface in the pore. The location of the nanorobot 114 isrecorded each time it stops or changes direction to identify the contactpoint 154. In one embodiment, the mere presence of the nanorobot 114 canact as a sensor. By determining the location of the nanorobot, thecomputer 126 can determine that the robot is in a pathway that has adiameter or cross-section that is at least as large as the nanorobot.Thus, the pathways can be mapped even if the precise location ofsurfaces defining the pathway are not known. Furthermore, the locationsof surfaces defining the pathway can be approximated from the locationsof the nanorobots 114.

The features of a rock formation can also be measured by an ultrasonicsensor 158 (FIG. 8C), wherein the sensor emits an ultrasonic frequencyand then interprets the signals reflected back to the nanorobot 114, asshown in FIG. 12. Similarly, a radio frequency generator 160 on thenanorobot 114 can emit a radio frequency 162 that is reflected by thesurface 152 of the formation back to the nanorobot. The ultrasonic orradio frequency sensor each allows the nanorobot to map geologicalfeatures in its immediate area without directly contacting eachgeological feature. In some embodiments, the radio frequency generatorused for non-contact surface mapping can share components with the radiofrequency transmitter 136 used for communication.

In one embodiment, the nanorobot 114 has position sensors fordetermining its own position or movement. For example, vibration sensor205 can determine vibrations associated with movement and, thusdetermine the velocity and direction of movement of the nanorobot 114(FIG. 5). Other motion or position sensors 206, such as, for example, anano-sized accelerometer, can be used to determine the location orrelative movement of the nanorobot 114 within the formation.

The nanorobot can require power to perform its tasks. Some embodiments,however, do not require a power supply or power source to be located onor in the nanorobot 114. For embodiments that require power, numerouspower sources are available to power the nanorobot 114, examples ofwhich are illustrated in FIGS. 5, 6, and 9. Various types of powersupplies 208 can capture power from these power sources. For example,power can come from thermoelectric power created by the hightemperatures of the subterranean environment. Power can also come frompiezoelectric generators, which generate power in response tocompression or vibration of a surface. The piezoelectric generator caninclude a crystal that gains an electrical charge when a force isapplied to the crystal. Well fluid can cause the piezoelectric generatorto vibrate and thus create electricity to power the nanorobot.Furthermore, the same crystal can vibrate in response to an electriccharge applied to the crystal. The vibration may be sufficient to giveoff an ultrasonic signal, which could be used to drive a propulsiondevice. Therefore, stored power in the nanorobot could be used toprovide power and thus the single piezoelectric generator can provideboth electricity and propulsion for a nanorobot.

Similarly, fluid movement in the vicinity of the nanorobot 114 can causean electromechanical nanoactuator to move and thus generate electricity.In another embodiment, power is generated by CNT based fuel-cells. Thefuel-cells generate power from in-situ hydrocarbon. Some power can beproduced by friction with rock surfaces. In some embodiments, ATPasesare used to power or partially power some sensors. An ATPase is a classof enzymes that catalyze the decomposition of various chemicals, causingthe chemicals to release energy as they decompose.

Power from these various power supplies 208 can be stored in batteries212 such as, for example, CNT-based batteries. Furthermore, power can bestored in batteries prior to inserting the nanorobots 114 into theground. In one embodiment, nanorobots are able to recharge at a downholecharging station 210 (FIG. 17). The downhole charging station could be,for example, a battery charger located in or on the casing 104 in thewellbore 100. The nanorobots 114 can propel themselves or be propelledto the charging station 210. In this embodiment, the power supply 208receives electrical power from the charging station 210. The powersupply can operate by contact or non-contact techniques. After the powersupply 208 recharges the battery 212 or batteries 212, the nanorobot 114can move away from the power station 210 to continue its task.

Various propulsion devices 164, as shown in FIGS. 4-10, can be used topropel nanorobots through the rock formation. The nanorobot 114 is ableto move through pores 118 within the formation without becoming stuckinside the pore (and thus blocking fluid flow through the pore). Some ofthe propulsion devices are able to move the nanorobot through the rockformation even when not aided by downhole fluid flow. Furthermore, thepropulsion devices are able to overcome the viscous and gravitationalforces present within the formation. Some of the propulsion devices canpropel the nanorobot at a practical speed against the reservoir fluidflow. Finally, the propulsion devices are able to propel the nanorobotin any direction, including changing direction laterally and vertically.

The simplest propulsion device is a fluid-flow device, wherein fluids112 within the rock formation 102 propel the nanorobot. In thisembodiment, the nanorobots are injected into the reservoir with normalinjection water, as shown in FIG. 15. As the water 116 pusheshydrocarbons through the pores and pathways within the formation, thenanorobots 114 move with the water and hydrocarbons. The nanorobots inthis embodiment can have any shape, including, for example, a sphericalshape, as shown in FIG. 14. In one embodiment, spherical nanorobots 115having various sizes are used in a single formation. The larger diameternanorobots 115 are only able to move along pathways 120 in the formation102, while smaller diameter nanorobots 115′ are able to travel alongsmaller pathways 121. The pathways 120 accessible to all nanorobots 115,115′, are at least as large as the largest nanorobot 115. Pathways 121,being accessible to the smaller nanorobots 115′ but not nanorobots 115,are identified as being smaller than nanorobot 115 but larger thannanorobot 115′. The cross-section of each pathway is defined as thedistance, transverse to the path of the nanorobot 115, between thewalls, or surfaces, of the cavity. Finally, pathways 122 may be so smallthat they are not accessible to any nanorobots. As one of skill in theart will appreciate, the nanorobots 115, 115′, thus, serve as a type of“go/no-go” gage to measure the size of pathways within the formation102.

The powered propulsion devices 164, as shown in FIGS. 8A-8D can bepowered directly from the power supply 208, or the power supply powercan be routed through the onboard computer 124. A single nanorobot 114can have more than one powered propulsion device, and can use gravityand fluid flow in combination with the powered propulsion device.

In some embodiments, the propulsion device 164 includes one or morepropellers 166. The propeller 166 can be a molecular propeller withblades formed by planar aromatic molecules and a shaft comprising acarbon nanotube. One of ordinary skill in the art will appreciate thenano-motor required to rotate propeller 166. Any of the propulsiontechniques, including the propeller 166, can be used in conjunction withone or more rudders 234 to steer the nanorobot. Rudders 234 can be movedby, for example, signals from an onboard computer 124 to cause thenanorobot 114 to alter its trajectory.

In another embodiment, the propulsion device 164 can include flagella170. In this embodiment, the nanorobot has a leg-like or fin-shapedappendage similar to that of bacteria or paramecia. The flagella 170 canuse a biomimetic synthetic flagella composed of multiwalled carbonnanotubes.

In another embodiment, a rapidly vibrating membrane 168 can provide thenecessary thrust to propel the nanorobot. The vibrating membrane 168 canbe alternately tightened and relaxed to produce thrust. Because thenanorobot is so small, the thrust produced by the vibrating membrane 168can be sufficient to propel the nanorobot. Vibrating membranes 168 canbe located on more than one surface of the body 132 and, thus, used tosteer the nanorobot 114. For example, a nanorobot can have vibratingmembrane 168 on a rear surface to propel the robot 114 forward, and canalso have one or more vibrating membranes 168′ to cause lateral movementor to cause the nanorobot 114 to turn and move in a different directionthan its current trajectory, as shown in FIG. 8C.

As shown in FIG. 10, propulsion devices 164 such as propellers 166,membranes 168, and flagella 170 can each produce thrust 216 against awellbore fluid 112. In one embodiment, the nanorobot 114 moves in randomdirections 218 until it makes contact with a surface 152. Upon contact,the nanorobot moves in a different direction 220. In another embodiment,the nanorobot 114 can receive a signal to change direction 222 from, forexample, the control computer 126, or the onboard computer 124 of thenanorobot can determine that it is necessary to change direction. Inresponse to the signal 222 or determination 236 to change direction, thenanorobot 114 can use a thruster such as its flagella 170 or lateralvibrating membrane 168′ to cause it to change direction off of itscurrent axis of movement 224. Some embodiments can have a propeller 166that is offset from the center of the nanorobot body 132, which cancause a change in direction 226. In embodiments having a rudder 234, thenanorobot can move the rudder 234 in response to the signal to changedirection 236, 222 and thus cause a change in direction.

In still another embodiment, the propulsion device 164 can includecrawlers 214 wherein mechanical legs, such as carbon nano tube legs, aredriven by nano-motors to enable the nanorobot to “walk” within the rockformation, even in the absence of liquid fluids. In these embodiments,the nanorobot comes into contact with a surface 230 in the formation102, and the crawler 214 propels the nanorobot 114 along the surface232. Other variations of the propulsion device can include wriggling,rolling, and worm-like or gecko-like movement, all of which can beperformed within a fluid or in the absence of a fluid. There can beoverlap between a crawler 214 and other propulsion devices. For example,flagella 170 can propel the nanorobot through fluid 216, and can, atother times, contact a surface 230 and cause the nanorobot 114 to movealong the surface 232.

As one of skill in the art will appreciate, the propulsion devices canbe powered by various kinds of motors 238, including, for example,nano-motors and Brownian motors. Brownian motors are nano-scale ormolecular devices by which thermally activated processes (chemicalreactions) are controlled and used to generate directed motion in spaceand to do mechanical or electrical work. In one embodiment, a radiofrequency powered motor 240 is used to drive the propulsion device 164.In this embodiment, a radio frequency transmitter, which could be thesame transmitter used for communication, generates a signal that causesthe RF motor 240 to actuate.

The nanorobot 114 can have an onboard computer 124, as shown in FIGS. 5,6, and 9. In some embodiments, the computer 124 includes a processor244, memory 246, and an input/output device 248. The computer 124 couldbe a quantum computer, a nanotube computing system, a nanomachine, amolecular computer, or a combination thereof. The onboard computerprocessor 124 can have parallel processing capabilities.

The onboard computer 124 can serve as a controller for the nanorobot114. The controller can initiate and manage functionality within otheronboard components based on, for example, the data collected by thesensors. In an exemplary embodiment, sensor readings cause a responsefrom the nanorobot. In one example, when the sensor 138 detects ahydrocarbon, the controller 124 actuates the transmitter 128 and causesthe transmitter 128 to transmit the current location and the presence ofthe hydrocarbon to the wellbore fixed receiver 134. In another example,when the sensor 138 reading does not show a hydrocarbon, the controlleractuates the propulsion device 164, causing the nanorobot 114 to move toa new location.

The onboard computer 124 can also serve as a memory device. In the eventthat the nanorobot 114 is unable to transmit data regarding, forexample, its position or the presence of a hydrocarbon, the data isstored in the onboard computer memory 246 until the nanorobot 114 isable to transmit or until the data is otherwise downloaded to a datacollector. A data collector (not shown) includes a device to collectnanorobots from a collection point, such as in production fluid, extractthe nanorobots 114, and then download the memory of the nanorobots intoa computer memory.

The nanorobot can have communication abilities, such as a radiofrequency transmitter 128 and a radio frequency receiver 130. Thetransmitter 128 and receiver 130 are best shown in FIGS. 5, 6, and 9.The nanorobot computer can control the transmitter 128 and directsignals to the transmitter for transmission. The nanorobot computer canalso receive data through the receiver 130. An antenna 131 may beconnected to or integral with the transmitter 128 and receiver 130. Inone embodiment, the receiver 130 and transmitter 128 are the samecomponent—a reactive identification tag 133, such as a radio frequencyidentification tag or radio frequency identification device (“RFID”).The radio frequency identification tag receives a signal and, inresponse to the signal, transmits a signal.

The nanorobot uses the radio frequency transmitter 128 to transmitvarious data to receivers 532, such as fixed receivers 134 located inthe wellbore 100. The radio frequency transmitter transmits, and thefixed receiver receives, radio frequency transmissions at preselectedfrequencies. The transmitted data could include, for example, thepresence or absence of hydrocarbons, the type of hydrocarbon encounteredby the nanorobot, the pressure and temperature inside the formation, andthe position of the nanorobot 114.

In an exemplary embodiment, the nanorobot 114 has a radio frequencyreceiver 130. The nanorobot receiver 130 receives signals, for example,from fixed transmitters 136 located in the wellbore 100. The transmittedsignals could include, for example, instructions directing the nanorobot114 to move in a different direction or to a different specifiedlocation.

In some embodiments, the nanorobot can have a payload bay 140 fordelivering a payload 142 to a location inside the geophysical formation102, as shown in FIG. 13. The payload 142 could be, for example, asurfactant used to change the surface tension of the fluid inside theformation. Alternatively, the payload 142 can be a matrix acidizing ordamage removal fluid, a formation consolidation chemical for sandcontrol, or a polymer for conformance control. In one embodiment, thepayload 142 includes a swelling hydrophilic polymer for obstructingundesirable pathways. The payload bay 140 can have one or more doors 250which protect the payload during travel. When the nanorobot reaches thedelivery point, the payload doors 250 can open to release the contents.In one embodiment, the payload door 250 forms a hermetic seal to preventfluids from contacting the payload 142 prior to opening the door 250.

The payload delivery point can be determined by a variety of devices. Inone embodiment, the sensor 138 or on board computer 126 can open thedoor when the sensor 138 detects a predetermined condition. For example,if the sensor 138 detects crude oil having a viscosity higher than apredetermined amount, the sensor sends a signal to the payload door 250actuator, causing the payload door to open. Alternatively, the onboardcomputer 124 could open the payload door 250 when the nanorobot 114reaches a predetermined location. In still another embodiment, a signaltransmitted from the above-ground nanorobot control computer 126, viathe wellbore fixed transmitters 136, directs the payload door 250 toopen. In one embodiment, an electromagnetic signal from the wellborefixed transmitters can actuate the payload door 250. One of skill in theart will appreciate the usefulness of being able to deliver variouspayloads into the pores of a geophysical formation.

FIGS. 5, 6, and 9 show exemplary embodiments of the interconnections andwiring between various components within the nanorobot body 132.Furthermore, FIG. 9 shows wireless signal connections between thenanorobot and the wellbore transmitters 136 and receivers 134. The powersupply 208 can provide power to the computer 124. In some embodiments,the computer 124 provides and controls the application of power to othercomponents, such as the onboard receiver 130, the propulsion device 164,and the sensor 138. In other embodiments, the power supply can providepower directly to the components such as the propulsion device 164.

The nanorobots 114 can be inserted into the geophysical formation 518and inserted into the rock pores by a variety of devices. For example,the nanorobot can be placed in water 116 or fluid used for secondaryrecovery operations (FIG. 15). The nanorobot-containing water isinjected into the reservoir or rock formation 102, thus carrying thenanorobots 114 along the same pathways used by the pressure-injectedwater. One skilled in the art will appreciate that the nanorobots can beinserted through a discovery well, a production well, a water-injectionwell, a well drilled for the sole purpose of inserting probes, or anyother routes into the geophysical formation. This technique is usedanticipating that the injected nanorobots will flow into, and along,permeability pathways 120, as shown in FIG. 3 (the enlarged section ofFIG. 3 is drastically enlarged—the nanorobots 114 are less than 500nanometers wide).

Alternatively, the nanorobots can be placed in a carrier 252, such as acylinder or a running tool attached to the drill string or lowered on acable 254 through the wellbore 100. The carrier can have doors that opento release or deploy the nanorobots 114 at various locations within thewellbore 520. The wellbore can be perforated as appropriate so that thenanorobots 114 can move through the perforations 256 through the sidesof the wellbore. If the existing wells are not in the correct location514 for inserting nanorobots 114, an additional insertion well orexploratory well may be drilled 516.

An alternative insertion method is to place the nanorobots 114 in thedrilling mud (not shown). Drilling mud is used to lubricate theearth-boring drill bit. Drilling mud also carries spoil (earth and rockdislodged by the bit) up to the surface. Nanorobots can be placed in thedrilling mud before the mud is injected into the wellbore. Thenanorobots then travel through the sides of the wellbore into the rockformation.

The nanorobots can also travel ahead of the drill bit (not shown), intothe rock that is going to be drilled. In this application, the nanorobottransmits data regarding the rock that is about to be drilled back tothe surface. Real time downhole mud properties, formation stress, andborehole stability data can be transmitted during drilling operations.This data could be helpful for geosteering and well placement. In someembodiments, the nanorobots are sent ahead of the drill bit to collect“true formation data” before the drill bit and mud alter the formationcharacteristics.

FIG. 17 illustrates embodiments of several techniques to release 258nanorobots 114 into a formation 102. If the release technique uses waterdrive insertion 260, the nanorobots are first placed in the drive water262. Water is used for illustration only. Other types of drive fluid canbe used. The drive water is injected into the formation 264, thenanorobots 114 being injected with it. Additional water (or drive fluid)can be injected 266 after the nanorobots 114 are released to cause thenanorobots to move further into the formation 102.

If the wellbore carrier 252 is used for insertion 268, the nanorobotsare first placed into the carrier 270 and then the carrier is loweredthrough the wellbore 100, or another borehole into the formation 102, tothe desired depth 272. The carrier then ejects the nanorobots from thecarrier 252 into the wellbore 274. If drilling mud is used to insert thenanorobots 276, the nanorobots are first placed into the drilling mud278 and then the drilling mud is pumped into the wellbore 280. Oncereleased, the nanorobots from the carrier or the drilling mud can becaused to move into the formation 102, by, for example propellingthemselves through cavities in the formation 282.

As shown in FIG. 18, the wellbore 100 is lined with a casing 104, suchas a metal tube. Multiple fixed receivers 134 can be attached to thecasing 104 or embedded within the casing 104. The fixed receivers 134can be spaced apart longitudinally along the casing 104. The fixedreceivers 134 can also be spaced apart around the circumference of thecasing 104. The wellbore 100 can also be lined with fixed transmitters136 for transmitting data to the nanorobots 114. The fixed transmitters136 are longitudinally spaced apart along the casing 104. The fixedtransmitters 136 can be co-located with the fixed receivers 134 or becombined in the same housing with the fixed receivers 134. Fixedreceivers 134 and fixed transmitters 136 can also be located on thesurface, as shown in FIG. 2. The fixed receivers 134 and fixedtransmitters 136 can be powered by, for example electricity frombatteries or wires passing through or embedded in casing 104.

As shown in FIGS. 2 and 9, each nanorobot onboard transmitter 128 cantransmit data to one or more fixed receivers 134 located in the wellboreor on the surface. The fixed receivers 134, in turn, can transfer thedata to control computer 126 for processing and analysis. The controlcomputer 126 can be located on the surface. Similarly, the controlcomputer 126 can send information to the nanorobots 114. The informationfrom the control computer can be broadcast by the fixed transmitters 136located in the wellbore or on the surface. In one embodiment, if thenanorobot 114 is unable to transmit to an fixed receiver 134, thenanorobot 114 can store the information for later transmission.

In some embodiments, signal cables such as wires or fiber optic cablestransfer data from the fixed wellbore receivers 134 to the controlcomputer 126. In other embodiments, the fixed wellbore receivers canwirelessly transmit data to the control computer 126 using, for example,radio frequencies. Some wireless fixed receivers may be unable todirectly communicate with the control computer 126 because, for example,the fixed receiver 134 is located too far below the surface. In oneembodiment, fixed receivers 134 have a relay transmitter and are able totransmit data to another fixed receiver 134′, as shown in FIG. 20. Thesecond fixed receiver 134′ is then able to relay the data to the controlcomputer 126, or to subsequent fixed receivers 134. Thus the fixedreceiver 134 that is in communication with a nanorobot 114 can relaydata through other fixed receivers 134′ to the surface. Similarly, inthe event a fixed transmitter is unable to communicate with the controlcomputer 126, other fixed transmitters 136′ can relay the signal to thefixed transmitter 136 that is in communication with a nanorobot 114.

As shown in FIGS. 2 and 9, the fixed transmitters 136 can transmitinstructions and data to the nanorobots 114 such as instructions tochange direction or move to a specific location. The fixed transmitters136 can send information that is received by the onboard receiver 130 ofthe nanorobot 114. The transmitters can also transmit a locating beaconwhich a nanorobot 114 can use to determine its own position.

The nanorobot deployment can use swarm characteristics, whereinhundreds, thousands, or even billions of nanorobots work together to mapthe formation 102, as shown in FIG. 2. The nanorobots can dispersethroughout the formation 102, or can concentrate as a swarm 286 in onearea of interest. The nanorobots 114 can all be the same, or differenttypes of robots with different types of sensors can be employed. In someembodiments, the nanorobots 114 communicate with each other.

In some embodiments, an individual nanorobot 114 may not be able tocommunicate with any fixed transmitters 136 or receivers 134. In oneembodiment, nanorobots are able to relay data from other nanorobots, asshown in FIGS. 2 and 19. In one embodiment, if a nanorobot 114 is toofar from a receiver 234 to transmit a signal, the nanorobot 114 can sendits data to another nanorobot 114′, as shown in FIG. 19. Nanorobot 114′,in turn, transmits the data to the fixed receiver 134. In oneembodiment, nanorobots can form a chain where the signal is transmittedthrough multiple relay nanorobots 114′ back to the wellbore receiver134. Similarly, multiple nanorobots 114′ can relay a message from awellbore fixed transmitter 136 to a distant nanorobot 114.

In some embodiments, multiple wellbore radio frequency fixed receivers134 can receive a signal from the nanorobot 114, in which case thecontrol computer 126 can use the received signals to triangulate theposition of the nanorobot, as shown in FIG. 20. In this embodiment, eachwellbore receiver 134 can determine the direction of the signal from thenanorobot 114. By mapping the intersection of two or more directionsignals 288, the control computer 126 can determine the location of thenanorobot 114. Preferably, three direction signals are used to determinean accurate three-dimensional location of the nanorobot 114. Inembodiments having a reactive identification tag 133, the wellbore fixedtransmitter 136 can transmit a signal that causes the reactiveidentification component to emit a signal. A wellbore fixed receiver 134can detect the emitted signal from the reactive identification tag 133,and use the signal to determine the direction to the nanorobot 114. Whentwo or more wellbore fixed receivers 134 detect the emitted signal, theycan triangulate to determine the position of the nanorobot 114. Becauseeach reactive identification tag 133 can emit a unique signal, thecontrol computer 126, upon receiving the signal data from the wellborefixed receivers, can determine the location of a particular nanorobot114. The control computer 126, thus, can track the location of aparticular nanorobot 114 over time to determine the path traveled by thenanorobot 114. For triangulation, the fixed transmitters 136 and fixedreceivers 134 may all be located in the same wellbore 100, or a portionof the fixed transmitters 136 and fixed receivers 134 could be locatedin a different wellbore 100 or on the surface. As shown in FIG. 20,signal 137 can pass from an a fixed transmitter 136 in one wellbore tofixed receiver 134 in a different wellbore. The location of nanorobot114 is determined by the point that signal 137 contacts nanorobot 114.In one embodiment, the triangulation can work using beacon signals fromthe wellbore fixed transmitters 136. Each transmitter 136 emits a uniquesignal. The nanorobots 114 receive the unique signals using the onboardreceivers 130 and are able to triangulate their own position, from thebeacons, using the onboard computer 126.

As shown in FIG. 20, a nanorobot 290 may be too far from the wellbore totransmit a signal to the wellbore receivers 134. In one embodiment,however, the nanorobot 290 can transmit to other nanorobots 114. Becausethe location of the other nanorobots 114 is known, the other nanorobots114, thus, can triangulate to determine the location of nanorobot 290,and then transmit the location of nanorobot 290 back to the wellborereceiver 234.

One or more control computers 126 are used to receive data from thenanorobots, interpret the data from the nanorobots, and control anddirect the nanorobots. An exemplary embodiment of a control computer 126is shown in FIG. 22. The one or more computers providing these functionsare referred to collectively as the “control computer.” In someembodiments, the control computer includes an operational controlcomputer and a geophysical mapping computer. In other embodiments, thecontrol, analysis, and mapping functions are performed by a singlecomputer. The nanorobot control computer 126 collects data from thenanorobots 114. The control computer 126 can use this data to identifyfluid properties 535 and the location of pathways 538. The data can comefrom the fixed receivers 134 located in the wellbore or above ground, orthe data can be offloaded from the nanorobot 114 after the nanorobot isrecovered.

The nanorobot control computer 126 is a machine that can include adisplay 292, a processor 294, an input/output device 296, a memory unit298, and a set of instructions 300 stored in a non-transitory,computer-readable storage medium with an executable program, as shown inFIG. 22. The non-transitory computer readable storage medium can be themachine memory 298, or it can be a separate storage medium for loadingonto the machine. When executed by the machine, the program product 300can cause the machine to perform the following tasks: Nanorobot Director302; Formation 3D Mapper 304; Pathway Mapper 306; Fluid Mapper 308;Hydrocarbon Locator 310; Gas Plume Mapper 312; Potable Water locator 314and Surface Approximator 491. Functions in any of the sets ofinstructions can be included in other sets of instructions.

The Nanorobot Director 302 set of instructions sends information anddirections to the nanorobots 114. Preliminary data from the nanorobotscan indicate an area of particular interest within the formation (“areaof interest”). The nanorobot control computer can send instructions, viatransmitters, to nanorobots in the formation, directing the nanorobotsto move to the areas of particular interest. The nanorobot controlcomputer can also interpret data regarding hydrocarbon characteristicsand formation structure, and then instruct payload-carrying nanorobotsto a specific location and then order the nanorobots to discharge theirpayload at that location.

In one embodiment, shown in FIG. 23, the control computer 126 firstdetermines 302 whether it is receiving data from a nanorobot 114 or froma particular nanorobot 114. If it is not, it will send a signal, orping, the nanorobot to establish communication or wait until it receivesdata 304. (The term geophysical nanorobot is abbreviated as “GNR” insome drawings). Any time that any program product receives data from ananorobot, the data can come from any technique. For example, the datacan be in real time or near real time, wherein the data is transmittedfrom the nanorobot 114 to a wellbore receiver 134 and relayed from thewellbore receiver 134 to the control computer 126. Alternatively, thedata can be stored in the nanorobot computer as it is acquired anduploaded to the control computer at a later time. Upon receiving datafrom the nanorobot, the computer can determine the location of thenanorobot 306. The location can be determined by, for example,triangulation from wellbore receivers 134 or from position data storedin the nanorobot. The computer 126 can determine whether the nanorobotis in contact with a surface within the formation 308. If so, thecomputer will record the location of the nanorobot's position at thetime of surface contact to establish a location of a point on thesurface 310. The computer 126 can then determine whether the nanorobot114 is moving in the correct direction 312, such as towards apredetermined area of interest. If so, the computer will allow thenanorobot to keep going. If not, the computer 126 will send a changedirection instruction signal through the fixed radio transmitters 314and then wait until it again receives data from the nanorobot 302. Thenanorobot will propel in a direction different than its currenttrajectory responsive to the instruction from the machine transmittedvia the fixed radio transmitters and thus, for example, move toward anarea of interest. The computer can also record the type of fluid incontact with the nanorobot 316. The computer can receive raw sensordata, such as the amount of resistance measured by the nanorobot'selectrode, or it can receive more specific fluid-type data from thenanorobot. When recording the type of fluid at step 316, the nanorobotcan also record the location of the fluid based on the nanorobotslocation at the time of contact with the fluid (from step 306). At step308, if the nanorobot is not in contact with a surface in the formation,the computer 126 will still record the nanorobot's position at step 318.If the nanorobot is carrying a payload 320, the computer determineswhether the nanorobot is in the correct position to dump the payload322. If so, the computer instructs the nanorobot to dump the payload324. In one embodiment, the computer first identifies a plurality ofcavities in communication with one another, each cavity having across-sectional area greater than a predetermined value to define apathway. Then, upon determining that a pathway exists, the computercauses a portion of the nanorobots located with in the pathway torelease their payload within the pathway. This could be done, forexample, if the payload is a swelling hydrophilic polymer and it isdesirable to obstruct the pathway. If not, or if the nanorobot is notcarrying a payload, the computer determines whether the nanorobot ismoving in the correct direction at step 312. If the nanorobot has anon-contact surface sensor, such as an ultrasonic sensor 158 or RFsensor 160, the computer 126 records information from the reflectedsensor signal in step 326.

The Formation 3-D Mapper 304 set of instructions creates a threedimensional map of the geological formation. The nanorobot controlcomputer combines the data from one or more nanorobots and uses it tocreate a three dimensional map of the formation. The map will indicatethe edges of the reservoir and the fluid contacts for the field. TheFormation 3-D Mapper 97 is able to update the map in real time. Featureson the map can include hydrocarbon location, water location, pore size,etc. The mapping program 304 can include instructions for floodmonitoring, which can map the progress of water through the reservoirduring hydrocarbon extraction operations.

In one embodiment, shown in FIG. 24, the formation 3-D Mapper 304performs the following steps. The computer first receives data from thenanorobot at step 330. If no data is available, it waits for data atstep 332. If data is available, the nanorobot determines whether it isnon-contact scanner data 334. If so, it receives the scanner data 336and plots the data on a 3D map 338. Scanner data, being data actuallyreflected from interior points in the formation, is a sensed threedimensional location. If there is sufficient data density to create a 3Dmap 340, the computer plots the scanned data 342. If there is notsufficient data at 340, the computer requests and waits for moreinformation 332. If the forthcoming data is contact sensor data at 334,the computer determines whether the nanorobot is in contact with asurface at 346. If not, the computer determines the nanorobot isfloating within a cavity and thus identifies open cavity space at 346.If the nanorobot is in contact with a surface, the control computerplots the surface contact point on the 3D map 350. Each actual contactpoint is a sensed three dimensional location of a surface within theinterior of the geophysical formation, in that the location was sensedby the nanorobot. The sensed three dimensional location of at least onepoint on each of a plurality of interior surfaces within the geophysicalformation, thus, is interior surface location data. The surface contactpoints and open cavity space data are combined to create a 3D map at352. In one embodiment, wherein the nanorobots do not signal actualcontact with the surface, the point on an interior surface can bedetermined by the presence of the nanorobot and a go/no-go indicationfrom the nanorobot. If a nanorobot of a given size is present at thatlocation, then the cross-section of the cavity at that location is atleast as big as the nanorobot. The surface locations at that location,thus can be approximated round the location of the nanorobot. Surfacelocations near the contact points are interpolated from the contact andcavity data at 354. The machine, thus, generates an interpolated map,responsive to the interior surface location data, by projecting surfacesbetween representations of the at least one points on each of theplurality of interior surfaces of the geophysical formation, theinterpolated map identifying a physical shape and a location of aplurality of surfaces in the geophysical formation. If the data densityis not sufficient to develop a map, the computer requests and waits fordata at 332. If it is sufficient, a 3D map is developed at 358. The 3Dmap from contact data and/or the 3D map from non-contact data is used toidentify the edges of the reservoir at 360. The locations of fluidsidentified by the nanorobots are added to the reservoir map at 362. Thecomputer then determines whether dark regions exist on the map. A darkregion is an area where no data is available from nanorobots—becausenanorobots have not yet explored the cavities, the receivers are notable to receive information from the nanorobots, or because the regionis solid and not accessible to nanorobots. If no dark regions exist, thecomputer continues to receive data from the nanorobots to monitor theextent of fluid movement, such as the extent of water drive orfloodwater movement. If dark regions exist and the computer determinesnanorobots should be able to provide data, the computer can instructnanorobots to move toward the dark region at step 368 and then wait fordata at 332.

The Fluid Mapper 308 set of instructions can plot the locations offluids on the map and identify and monitor various fluid properties. Inone embodiment, shown in FIG. 25, the computer first receives 3D mapinformation at step 372. The instructions then cause the computer tocreate a fluid map by plotting the type and location of fluids onto theinterpolated map of the geophysical formation so that physicalrepresentations of fluids within the geophysical formation are displayedon the computer 374. From the fluid locations and the map of thecavities in the formation, the computer can then identify the edges ofthe reservoir at 376. The computer can then use fluid data, such as thepressure of the fluid at various locations, and assign pressures tofluid regions on the map at 378. As water or other drive fluids movethrough the formation, the computer can monitor the extent of the wateror fluid movement at step 380. Finally, the fluid mapper instructionscan cause the computer to model the current and future flows of fluidsthrough the formation based on the fluid data and the cavity data, atstep 382.

The Pathway Mapper 306 set of instructions locates pathways through theformation 538. The computer program interprets data from swarms ofnanorobots moving through pathways within the formation. The dataincludes the nanorobot's movement, trajectory, and velocity. Thecomputer program also considers nanorobot sensor readings, such asultrasonic sensors and contact with rock surfaces. The data is combinedto create detailed maps of pathways and pores within the formation. ThePathway Mapper 306 set of instructions also identifies high permeabilitypathways within the formation. When water is injected for secondaryrecovery, the pressurized water tends to flow through large pathways.The water may take a circuitous route through several high permeabilitypathways from the injection point to the hydrocarbon extraction point(the production well). These pathways frequently bypass substantialamounts of hydrocarbons. The computer program is able to integratepathway data from multiple nanorobots to form a model of the pathways.In some embodiments, the model can identify locations for productionwells and injection wells to achieve maximum extraction of hydrocarbons.The computer can use data from the nanorobots to map “thieve zones” orhigh-permeability “super-K” zones within the reservoir. This data can beused to enhance conformance control and water shut off operations. Thenanorobot can also identify the locations of pathways through theformation. Some pathways are larger than others. Water-drive water maypass through the larger pathways while bypassing hydrocarbon deposits.The pathway mapper instructions can cause the control computer toidentify such large pathways based on data from the nanorobots. Thecomputer can also use the data to create a pore network model (“PNM”)that depicts the entire pore network of the formation.

In one embodiment, the Pathway Mapper 306 causes the computer to performthe following instructions, as shown in FIG. 26. The computer receives3D map data at step 384. The data can include the locations of cavities,or pores, within the formation, and the locations of the surfaces thatdefine the cavities. The computer analyzes the cavity data to identifycontinuous series of cavities 386. These are cavities that are incommunication with one another, such that fluid can flow through all ofthe series. The computer then determines whether, for any continuousseries of cavities, any cross sectional area is smaller than apredetermined amount 388. A small cross sectional area serves as a chokepoint that restricts fluid flow. If a small cross sectional area exists,the series of cavities is identified as a pathway at step 390. In oneembodiment, the program instructs the computer to identify a pluralityof cavities in communication with one another, wherein each of thecavities has a cross-sectional area larger than a predetermined value.The cross-sectional area is the area located between outer surfaces, orwalls, of the cavity, transverse to the path of a geophysical nanorobottraveling through the cavity. The plurality of cavities in communicationwith each other and all having a cross-sectional area larger than apredetermined value is defined as a pathway.

In one embodiment, geophysical nanorobots having a substantiallyspherical shape are used to identify the sizes of pathways. Thenanorobots can have a plurality of different size diameters. A uniqueradio frequency identification tag can be used for each nanorobot or foreach different size diameter. The program can instruct the computer toidentify a location within the formation accessible to a first set ofthe plurality of geophysical nanorobots having one of the differentsized diameters, but not accessible to a second set of the geophysicalnanorobots having another one of the different sized diameters.

If a continuous series of pathways does not have any cross sectionalarea less than a predetermined amount (X), then the continuous cavitiesare marked as a high speed pathway in 400. In other words, if aplurality of cavities are in communication with each other, and eachcavity has a cross-sectional area greater than a predetermined amount,the computer defines it as a pathway. The computer then identifiescontinuous high speed pathways between a water injection location andthe extraction wellbore in 394. A high speed pathway linking theinjection and extraction points could cause water drive fluid to bypasspockets of hydrocarbons. After mapping pathways and high speed pathways,the computer determines whether all pathways are mapped at 398. If so,the pore network model can be developed at 396. If not, the computerreceives more data at 384 to further develop the models. The computercan also receive velocity data from the nanorobots at 402. In someembodiments, nanorobots can determine their own velocity. In otherembodiments, the control computer can determine nanorobot velocity fromwellbore receiver positional data (triangulation) received over a periodof time. If the velocity of a nanorobot is greater than a predeterminedamount (Y) for a specified length of time, the computer can use thatdata to conclude the nanorobot is traveling along a high speed pathwayand, thus, map the pathway as such at 392. Data regarding the size andlocation of pathways can be used, for example, to determine thelocations of future drive or extraction wellbores.

The Hydrocarbon Locator 310 set of instructions uses data from thenanorobots 114 to locate deposits of hydrocarbons 110. The map canindicate the types of fluid present in the various regions of thegeophysical formation in which the nanorobots are located. In anexemplary embodiment, the computer program three-dimensionally plots alocation point from each nanorobot, along with the rock formation typeand fluid type reported by the nanorobot for that location. This can beperformed by the computer executing instructions from the FormationMapper program. By using data from hundreds or thousands of nanorobots,the computer is able to interpolate a complete map of the geologicalformation and its contents, including a three dimensional perimeter ofeach hydrocarbon formation 536. One of the mapping functions is todetermine the location of bypassed hydrocarbon deposits 540. One skilledin the art will appreciate the importance of determining the location ofsuch deposits.

In one embodiment, shown in FIG. 27, the Hydrocarbon Locator 310 set ofinstructions causes the computer to receive 3D formation map datacreated in response to the Formation Mapper 304 set of instructions 406.The computer then receives fluid data from the nanorobots 408. The fluiddata includes the types of fluid and, thus, whether or not the fluidsare hydrocarbons. The type and location of each fluid is recorded at 410and plotted on the 3D map at 412. From this data, the computer caninterpolate areas to indicate the presence of and type of fluid in eachcavity at 414. The computer then identifies regions where a plurality ofcavities are in communication with each other at 416. By determining thefluids in each cavity 414 and the cavities in communication 416, thecomputer can identify cavities in communication having a homogenousfluid type 418. The computer, thus, identifies a three-dimensionalregion filled with a homogenous fluid to define a fluid pocket withinthe geophysical formation. If the cavities with a homogenous fluid type,together, have less than a predetermined volume of fluid 420, the fluidsare plotted on the map at 422. If the cavities with homogenous fluidshave greater than a predetermined amount of the fluid, the computerdetermines whether the fluid is in communication with the wellbore at424. If so, the fluid is mapped as a fluid pocket at 426. If not, thefluid is mapped as a bypassed fluid pocket at 428.

The Gas Plume Mapper 312 set of instructions uses data from thenanorobots 114 to map the locations and movements of gas plumes withinthe formation. In an application wherein the nanorobots enter a porousgeological formation used to store a gas, such as carbon dioxide ornatural gas, the control computer can be used to create maps and modelsdepicting the travel of the gas plume within the rock formation. Thedata from the nanorobots sensors can be used to monitor how much of theinjected gas goes into solution with in situ fluids and whether and howit affects the chemical and physical properties of the fluids.Furthermore, the data can show how a rock mineral reacts with injectedgas. The plume and pressure data can be interpreted to show whether gasis leaking out of the storage facility to the surface or to an adjacentrock formation.

In one embodiment, shown in FIG. 28, the Gas Plume Mapper 312, whenexecuted, causes the computer to perform the following instructions. Thecomputer receives Formation Data from the Formation Mapper 304. Thecomputer also receives data from the nanorobots in step 434. This dataincludes fluid data that may not have been included in the FormationMapper data. The properties of the fluids, including type, location, andpressure, are recorded by the computer in 436. The coordinates of eachfluid are plotted on the 3D map 438. The computer then interpolates thepresence and type of fluid in each cavity 440. The computer determineswhether the identified fluid is a gas of interest 442. If not, thecomputer receives additional data from the nanorobots until it receivesinformation regarding a gas of interest. If a fluid is a gas ofinterest, the locations of the cavities having the gas of interest areidentified on the 3D map 444. The computer receives fluid property dataregarding other fluids that may be in the same cavities that contain thegas of interest 446. From this data, the computer determines whether thegas of interest is dissolved in the other fluid 448. If so, the computercan determine the percent of gas present in the other fluid 450. Thecomputer can also determine whether properties of the other fluid areknown, such as in a database 452. If so, the known properties of theother fluid can be evaluated to determine whether a reaction between thefluids is likely and the nature of any reaction 454. After mapping thelocations of cavities having gas of interest at step 444, the computercan receive additional geophysical property data from the nanorobots456. The additional data can include, for example, data regarding thetype of rock. This data, plus database data, can be evaluated by thecomputer to determine whether the rock material is likely to react withthe gas, and evaluate the type of any potential reaction 458. Also aftermapping cavities having the gas of interest 444, the computer canreceive pressure data, such as the pressure of the gas at variouslocations, from the nanorobots 460. With the pressure data and the 3Dmap, the computer can determine the volume of gas present in thecavities at 462. With the map showing location and pressure, thecomputer can determine the extent of the gas plume 464. Finally, thedissolution data, rock reaction data, and gas plume data can be combinedby the computer to predict the movement of the gas plume 466.

The Potable Water Locator 314 set of instructions uses fluid and mineraldata collected by the nanorobots 114 and transmitted to the nanorobotcontrol computer to find underground water sources and determine whetherthe water is potable water.

In one embodiment, shown in FIG. 29, the Potable Water Locator 314, whenexecuted, causes the computer to perform the following instructions. Thecomputer receives 3D formation map information from the Formation Mapperset of instructions 470. The computer also receives data from thenanorobots regarding fluids in contact with the nanorobots 472. If thefluid is not water, the computer waits until it receives additional data474. If the fluid is water, the computer determines from the datawhether the water is potable 476. This data can be determined, forexample, from fluid properties including resistance, pH, and bacteriaanalysis. If the water is not potable, it is plotted as a non-potablewater source on the map 478. If the water is potable, it is identifiedas a potable water source 480. The computer then identifies a pluralityof cavities having potable water that are in communication with eachother 482. Each plurality of cavities in communication with each otherand having potable water is mapped as a continuous formation of potablewater 484. The computer then determines whether the volume of thepotable water formation is greater than a predetermined value 486. Ifnot, the formation is mapped as a location of potable water. If so, theformation is mapped as a source of potable water 490.

In one embodiment, shown in FIG. 30, the Surface Approximator 491 set ofinstructions, when executed, causes the computer to perform thefollowing functions. In step 492, the computer receives the locations ofeach of the nanorobots over a period of time. The locations can bedetermined by, for example, triangulating, responsive to a signalreflected by each of the plurality of geophysical robots from one ormore transmitters associated with one or more wellbores to one or morereceivers associated with one or more wellbores. By receiving multiplelocations, over time, the computer can plot the path traveled by eachnanorobot within the formation 493. From the paths traveled by eachnanorobot, the computer can generate an interpolated map 494. Theinterpolated map can approximate the locations of surfaces bedetermining, from the traveled paths, where the nanorobots are not ableto travel and concluding that the nanorobots cannot travel through asurface. From the pathways, over time, the computer can estimate thevelocity of each of the nanorobots using a time/distance calculation.From this velocity, and knowing that the nanorobots are traveling withinthe fluid flow of the geophysical formation, the computer can estimatewith velocity of the fluid passing through each of the plurality oftraveled paths 495. If the nanorobot has a fluid sensor, the computercan receive the fluid data indicating the type at each of a plurality oflocations within the formation, and then plot the type of fluid on theinterpolated map to display a physical representation of fluids withinthe formation 496.

While the invention has been shown or described in only some of itsforms, it should be apparent to those skilled in the art that it is notso limited, but is susceptible to various changes without departing fromthe scope of the invention.

Furthermore, recitation of the term about and approximately with respectto a range of values should be interpreted to include both the upper andlower end of the recited range. As used herein, the terms first, second,third and the like should be interpreted to uniquely identify elementsand do not imply or restrict to any particular sequencing of elements orsteps.

Although the present invention has been described in detail, it shouldbe understood that various changes, substitutions, and alterations canbe made hereupon without departing from the principle and scope of theinvention. Accordingly, the scope of the present invention should bedetermined by the following claims and their appropriate legalequivalents.

The singular forms “a”, “an” and “the” include plural referents, unlessthe context clearly dictates otherwise.

Optional or optionally indicates that the subsequently described eventor circumstances may or may not occur. The description includesinstances where the event or circumstance occurs and instances where itdoes not occur.

Ranges may be expressed herein as from about one particular value,and/or to about another particular value. When such a range isexpressed, it is to be understood that another embodiment is from theone particular value and/or to the other particular value, along withall combinations within said range.

In the drawings and specification, there have been disclosed a typicalpreferred embodiment of the invention, and although specific terms areemployed, the terms are used in a descriptive sense only and not forpurposes of limitation. The invention has been described in considerabledetail with specific reference to these various illustrated embodiments.It will be apparent, however, that various modifications and changes canbe made within the spirit and scope of the invention as described in theforegoing specification and as defined in the appended claims.

The invention claimed is:
 1. A system to measure properties in ageophysical formation, the system comprising: a wellbore liningpositioned in a wellbore; a plurality of fixed radio frequency receiversspaced apart along the longitudinal extent of and connected to thewellbore lining to receive radio frequency transmissions at one or morepreselected radio frequencies; a plurality of transmitter assembliespositioned external to the wellbore lining and at a plurality ofsubstantially horizontally and vertically spaced apart locations withinthe geophysical formation, each of the plurality of transmitterassemblies including: a body, a sensor connected to the body andpositioned to detect the presence of one or more hydrocarbons within thegeophysical formation, a radio frequency transmitter connected to thebody, positioned to transmit positional data and hydrocarboncharacteristic data from the geophysical formation when the transmitterassembly is positioned therein, and a power supply connected to the bodyto supply power to the transmitter and the sensor, a machine incommunication with each of the plurality of fixed radio frequencyreceivers, the machine including a processor, a display in communicationwith the processor, and a non-transitory, computer-readable storagemedium with an executable program stored therein, wherein the programinstructs the processor to perform the following steps: receivingpositional data from each of the plurality of transmitter assemblies,the positional data indicating the location of the transmitterassemblies at a point in time and comprising interior surface locationdata received from a plurality of the transmitter assemblies, each ofthe interior surface location data defining a sensed three-dimensionallocation of a point on an interior surface within the geophysicalformation for the respective transmitter assembly; plotting, responsiveto receipt of the positional data, at least one positional data pointfor each of the plurality of transmitter assemblies; combining thepositional data from the plurality of transmitter assemblies to create arepresentation of a three-dimensional physical map of at least a portionof the geophysical formation, the physical map including an indicationof a three dimensional location of each of the plurality transmitterassemblies within the interior surface of the geophysical formation;receiving fluid data from each of the plurality of transmitterassemblies, the fluid data indicating the type and location of fluidlocated at each of the plurality of substantially horizontally andvertically spaced apart locations within the geophysical formation; andcreating a fluid map on the display by plotting the type and location offluids onto the physical map, the fluid map comprising pathways throughthe geophysical formation, pockets of hydrocarbons within thegeophysical formation, and interior surface boundaries of thegeophysical formation.
 2. A system as defined in claim 1, wherein atleast one of the fixed radio frequency receivers is positioned toreceive data from at least another one of the fixed radio frequencyreceivers when positioned in the geophysical formation and re-transmitthe data from the at least another one of the fixed radio frequencyreceivers to the machine.
 3. A system as defined in claim 1, furthercomprising a plurality of fixed radio transmitters connected to thewellbore lining, and wherein each of the transmitter assemblies includesa sensor assembly radio receiver connected to the body.
 4. A system asdefined in claim 1, further comprising a plurality of radio directionaltransmitters connected to the wellbore lining, each transmitting abeacon therefrom, wherein each of the plurality of transmitterassemblies further includes a transmitter assembly radio frequencyreceiver connected thereto, and wherein each of the plurality oftransmitter assemblies is configured to determine its positionresponsive to signals from the plurality of radio direction beacons. 5.A system as defined in claim 1, wherein each of the plurality oftransmitter assemblies further includes a transmitter assembly frequencyreceiver connected thereto, wherein one or more of the plurality oftransmitter assemblies is positioned to receive positional data from atleast another one of the plurality of transmitter assemblies andre-transmit the positional data from the at least another one of theplurality of transmitter assemblies to a fixed receiver in communicationwith the machine.
 6. A system as defined in claim 1, wherein thereceived positional data includes three-dimensional coordinates for eachof the plurality of transmitter assemblies at a plurality of timeinstances.
 7. A system as defined in claim 1, wherein thethree-dimensional physical map comprises an interpolated map generatedby projecting surfaces between a plurality of the points of the physicalmap, the interpolated map identifying a plurality of cavities in fluidcommunication with adjacent cavities.
 8. A system as defined in claim 1,wherein the received positional data includes velocity and trajectorydata from each separate one of a plurality of the transmitter assembliesat a plurality of time instances.
 9. A machine including a processor, adisplay in communication with the processor, and a non-transitory,computer-readable storage medium with an executable program storedtherein, wherein the program instructs the processor to perform thefollowing steps: receiving positional data from each of a plurality oftransmitter assemblies located in a geophysical formation, thepositional data indicating the location of the transmitter assemblies ata point in time and comprising interior surface location data receivedfrom a plurality of the transmitter assemblies, each of the interiorsurface location data defining a sensed three-dimensional location of apoint on an interior surface within the geophysical formation for therespective transmitter assembly; plotting, responsive to receipt of thepositional data, at least one positional data point for each of theplurality of transmitter assemblies to indicate a location of a cavityaccessible by a transmitter assemblies; generating a three-dimensionalinterpolated map by projecting surfaces between a plurality of thepositional data points, the interpolated map identifying a plurality ofcavities in fluid communication with adjacent cavities; receiving fluiddata from each of the plurality of transmitter assemblies, the fluiddata indicating the type and location of fluid located at each of aplurality of locations within the geophysical formation; and creating afluid map on the display by plotting the type and location of fluidsonto the interpolated map, the fluid map comprising interior surfaceboundaries of the geophysical formation.
 10. A method to measureproperties in a geophysical formation, the method comprising: lining awellbore in the geophysical formation with a wellbore lining, thewellbore lining having a plurality of fixed radio frequency receiversspaced apart along the longitudinal extent of and associated with thewellbore lining to receive radio frequency transmissions at one or morepreselected radio frequencies and a plurality of fixed radio frequencytransmitters spaced apart along the longitudinal extent of andassociated with the wellbore lining to transmit radio frequencytransmissions at one or more preselected radio frequencies; deploying aplurality of transmitter assemblies into the geophysical formation, eachof the plurality of transmitter assemblies including: a body, ahydrocarbon sensor connected to the body and positioned to detect thepresence of one or more hydrocarbons within the geophysical formation, aradio frequency receiver connected to the body, positioned to receiveradio frequency transmissions; a radio frequency transmitter connectedto the body, positioned to transmit positional data and hydrocarboncharacteristic data from the geophysical formation when the transmitterassembly is positioned therein, and a power supply connected to the bodyto supply power to the receiver, the transmitter, and the sensor;communicating, by a machine, positional data from each of the pluralityof transmitter assemblies, the positional data indicating the locationof the transmitter assemblies within the geophysical formation at apoint in time and comprising interior surface location data receivedfrom a plurality of the transmitter assemblies, each of the interiorsurface location data defining a sensed three-dimensional location of apoint on an interior surface within the geophysical formation for therespective transmitter assembly; plotting, responsive to receipt of thepositional data, on the machine, at least one positional data point foreach of the plurality of transmitter assemblies to indicate a respectivelocation of a cavity accessible by a transmitter assembly; generating athree-dimensional interpolated map on the display responsive to thelocation data by projecting surfaces between representations of thelocations of each of the plurality of transmitter assemblies within thegeophysical formation, the interpolated map identifying the physicalshape and location of inner-surface portions of the geophysicalformation; receiving fluid data responsive to the hydrocarbon sensorfrom a plurality of the transmitter assemblies, the fluid dataindicating the type and location of fluid located at each of a pluralityof locations within the geophysical formation; and creating a fluid mapon the machine by plotting the type and location of fluids onto theinterpolated map of the geophysical formation so that physicalrepresentation of fluids within the geophysical formation are displayedon the machine, the fluid map comprising interior surface boundaries ofthe geophysical formation.
 11. A method as defined in claim 10, themethod further comprising transmitting, via the radio frequencytransmitter connected to the transmitter assembly, hydrocarboncharacteristic data to one or more of the plurality of fixed radiofrequency receivers.
 12. A method as defined in claim 10, furthercomprising receiving data, via a first fixed radio receiver, transmittedby a transmitter associated with a second fixed radio receiver, andre-transmitting the data from a transmitter associated with the firstfixed radio receiver to the machine.